Impact of Confounding Thoracic Tubes and Pleural Dehiscence Extent on Artificial Intelligence Pneumothorax Detection in Chest Radiographs.

Journal: Investigative radiology
Published Date: Dec 1, 2020

Abstract

OBJECTIVES: We hypothesized that published performances of algorithms for artificial intelligence (AI) pneumothorax (PTX) detection in chest radiographs (CXRs) do not sufficiently consider the influence of PTX size and confounding effects caused by thoracic tubes (TTs). Therefore, we established a radiologically annotated benchmarking cohort (n = 6446) allowing for a detailed subgroup analysis.

Authors

  • Johannes Rueckel
    Department of Radiology, University Hospital, LMU Munich, Munich, Germany.
  • Lena Trappmann
    From the Department of Radiology, University Hospital, LMU Munich.
  • Balthasar Schachtner
    German Cancer Consortium, Heidelberg, Germany.
  • Philipp Wesp
    From the Department of Radiology, University Hospital, LMU Munich.
  • Boj Friedrich Hoppe
    From the Department of Radiology, University Hospital, LMU Munich.
  • Nicola Fink
    Department of Radiology, University Hospital, LMU Munich, Munich, Germany. nicola.fink@med.uni-muenchen.de.
  • Jens Ricke
    Department of Radiology, University Hospital Munich, Germany. Electronic address: jens.ricke@med.uni-muenchen.de.
  • Julien Dinkel
  • Michael Ingrisch
    Department of Radiology, Ludwig-Maximilians-University Munich, Munich, Germany.
  • Bastian Oliver Sabel
    From the Department of Radiology, University Hospital, LMU Munich.

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